Forecasting for regulatory credit loss derived from the COVID-19 pandemic : a machine learning approach
Marta Ramos González, Antonio Partal Ureña, Pilar Gómez Fernández-Aguado
| Year of publication: |
2023
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|---|---|
| Authors: | González, Marta Ramos ; Ureña, Antonio Partal ; Fernández-Aguado, Pilar Gómez |
| Published in: |
Research in international business and finance. - Amsterdam [u.a.] : Elsevier, ISSN 0275-5319, ZDB-ID 424514-3. - Vol. 64.2023, p. 1-14
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| Subject: | COVID-19 | Machine learning | Credit risk | Defaulted exposures | Internal-rating-based | Kreditrisiko | Künstliche Intelligenz | Artificial intelligence | Coronavirus | Epidemie | Epidemic | Insolvenz | Insolvency | Prognoseverfahren | Forecasting model | Wirkungsanalyse | Impact assessment | Kreditwürdigkeit | Credit rating |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.ribaf.2023.101907 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014280038